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Abstract

Introduction

We hypothesised that fatigue in rheumatoid arthritis (RA) is related to TNF-alpha
induced dysregulation of cerebral blood flow. Our objectives were to assess fatigue,
cognitive function and cerebral blood flow before and after initiation of anti-TNF
treatment.

Methods

In a pilot study, 15 patients initiating treatment with adalimumab were assessed for
fatigue using a visual analogue scale (FACIT-F), cognitive function using a panel
of psychometric tests and regional cerebral blood flow using MR perfusion imaging.

Results

Patients improved clinically after anti-TNF therapy in terms of DAS28 and FACIT-F.
Furthermore significant improvements were documented in full scale, verbal and performance
IQ following therapy. There was a non-significant trend towards reduced cerebral perfusion
in both grey and white matter, and fatigue at 3 months correlated with cerebral blood
flow in white (p = 0.014) and grey (p = 0.005) matter.

Conclusions

We demonstrate for the first time a significant improvement in cognitive function
following effective treatment of RA. Although we observed minor reductions in cerebral
blood flow, and a correlation between cerebral blood flow and fatigue, a larger, controlled
study would be required to affirm a causal relationship.

Introduction

Patients with rheumatoid arthritis (RA) report reduced health-related quality of life,
which is attributable to fatigue, pain and impairment of physical function. The fatigue
experienced is a pervasive symptom, which patients consider highly important [1]. It is a different experience to normal tiredness; patients frequently describe overwhelming
exhaustion as well as cognitive fatigue, hindering clear thought and concentration
[2]. Effective treatment of RA, particularly with biologic drugs, improves fatigue but
it is not clear if it also improves cognition [3]. While the improvement in fatigue is assumed to be a direct consequence of cytokine
reduction, the physiological substrate for such a profound effect is unclear.

TNF has been implicated in a number of neuropathologies [4]. A previous study into the effects of TNF on the brains of Wistar rats found that
a single intrastriatal bolus of TNF led to significant reductions (15 to 30%) in cerebral
blood volume, which was dependent on TNF type-2 receptor activation, and was preventable
with an endothelin receptor antagonist [5]. Neuroimaging studies in RA have identified hypoperfusion of the frontal and parietal
lobes, while in systemic lupus erythematosus, hypoperfusion of the frontal lobes has
been associated with cognitive dysfunction [6]. If TNF influences cerebral blood flow (CBF) in humans, then the chronically high
levels associated with active RA may be implicated in cognitive impairment. We therefore
hypothesised that treatment of active RA, particularly with TNF blockade, would lead
to improvements in both fatigue and cognitive function, and that these effects would
be related to changes in CBF. A small pilot study was initiated to address this possibility.
Advances in magnetic resonance imaging (MRI) technology and scanning techniques have
allowed direct and non-invasive imaging of CBF without the need for contrast injection.
We applied a CBF MRI technique in a cohort of RA patients about to commence a TNF
antagonist, and measured CBF, disease activity, fatigue and cognitive function before
and during treatment.

Materials and methods

This was an open-label pilot study. Cerebral MRI scans, fatigue scores, 28-joint disease
activity score (DAS28), and psychometric assessment were performed on patients before,
and 12 weeks into, anti-TNF therapy for RA. Ethical approval was granted by Newcastle
and North Tyneside 2 Research Ethics Committee. Funding was provided by Abbott Laboratories.
The funder was not involved with study design, performance or data analysis.

Patients

Fifteen patients with RA according to 1987 American College of Rheumatology (ACR)
criteria were recruited. Each had been identified as requiring anti-TNF therapy as
part of routine clinical care. Patients were excluded if they had previously received
any anti-TNF therapies or if they had contra-indications to undergoing cerebral MRI.
Adalimumab 40 mg was administered by subcutaneous injection every 2 weeks. The patients
otherwise received routine clinical care. The study was approved by the local research
ethics committee and all patients gave written, informed consent.

Psychometric testing

All patients completed a set of neuropsychometric tests at baseline and again after
12 weeks of treatment with adalimumab. The tests used were chosen to minimize any
learning effect and each session was administered by the same trained researcher to
avoid discrepancies in scoring. The selected tests (see below) were considered those
most appropriate for patients with fatigue.

The full-scale intelligence quotient (IQ) provides a summary of overall cognitive
ability and was obtained using a shortened version of the Wechsler Adult Intelligence
Scale III (WAIS-III), which assesses vocabulary comprehension, visuoconstructive ability
(block design), verbal reasoning (similarities) and nonverbal deductive reasoning
(matrices). Raw scores are compared with population age and sex normative values,
resulting in a T-score that is standardised to a mean of 100 and SD of 15.

Assessment of specific cognitive deficits using the WAIS-III

Three subtests of the WAIS-III were used to obtain non-standardised raw scores. The
digit span test assesses immediate recall for sequences of numbers increasing in magnitude.
The digit symbol search requires participants to indicate whether one of two symbols
is present in an array; this depends on paired associate learning (the ability to
deal with two stimuli at once and to be able to associate them). The patients also
completed a trail-making test of visual scanning, requiring a combination of information-processing
speed, manual motor speed, and sustained attention.

Fatigue

Fatigue was measured using the functional assessment of chronic illness therapy fatigue
scale (FACIT), a simple-to-administer questionnaire, which has been validated in RA
patients [8]. The range of possible scores is 0 to 52; greater scores reflect less fatigue.

MRI analysis

Perfusion images were processed into maps of quantitative regional cerebral blood
flow (rCBF) and corrected for image distortion. The rCBF maps were analysed in two
ways: (1) analysis of rCBF in grey and white matter was carried out to look for global
differences between patients in brain perfusion, and for changes with therapy. The
anatomical images were subjected to supervised tissue classification to define gross
regions of interest (ROI) for white matter, grey matter, cerebro-spinal fluid (CSF),
deep grey structures and any focal abnormalities. These ROIs were applied to the CBF
dataset to determine average flow in each tissue type; (2) statistical analysis by
group was applied to look for any regional differences or changes in perfusion. The
Statistical Parametric Mapping (SPM) software package (SPM 5) was used to transform
CBF data into a standardised brain space [9]. SPM was then applied to calculate pixel-wise group statistics between patients pre-
and post-therapy to determine areas of differences in rCBF, and to perform regression
analysis of clinical measures [10].

Statistical analysis

Statistical analysis was performed using SPSS (Version 15 - IBM Corporation, USA).
Tests for normality were performed using the Kolmogorov-Smirnov test. Interval data
were compared using Pearson's correlation coefficient, and ordinal data were analysed
using Spearman's correlation coefficient. Cognitive function and CBF at baseline and
12 weeks were compared using the paired t-test. DAS28 scores and FACIT fatigue were compared using the Wilcoxon signed-rank
test. Possible predictors of cognitive function were analysed as independent variables
using a forced entry method of multiple regression analysis. A P-value < 0.05 was considered statistically significant.

Results

Fifteen patients were recruited and thirteen completed all aspects of the study (Table
1). One patient inadvertently commenced adalimumab prior to baseline MRI, and one patient
stopped anti-TNF therapy after 6 weeks and declined further study participation. Analysis
was based on the paired datasets from the 13 patients completing the study; 12 patients
were female and one was male; the mean age of the group was 48.92 (SD 8.04) years.

Clinical response

All participants had a high level of baseline disease activity and fatigue (table
1). There were significant improvements in DAS28 (P = 0.002) and FACIT F score (P = 0.002) with adalimumab treatment. A significant relationship was observed between
age and baseline FACIT fatigue score (P = 0.03), increasing age corresponding with lower levels of fatigue, as well as between
baseline DAS28 and baseline FACIT fatigue score (P = 0.018) (higher DAS28 corresponding with greater fatigue).

Cerebral imaging

There was no significant influence of adalimumab treatment on either grey or white
matter CBF (P = 0.183 and P = 0.210 respectively, data not shown). SPM software applied to calculate group statistics
between patients pre- and post-therapy did not identify any focal areas of statistically
significant differences in rCBF.

Discussion

To our knowledge this is the first study to demonstrate an improvement in cognitive
function following effective treatment of RA. Improvements in cognitive function related
particularly to performance IQ, but we did not demonstrate a relationship with CBF,
fatigue or disease activity. The physiological correlate of improved cerebral function
therefore remains unexplained and requires further study. Although improvements followed
treatment with anti-TNF therapy, the lack of a control group in this small pilot study
preclude any conclusions being drawn regarding the specificity of the effect, and
future studies should incorporate additional treatment options.

There is a paucity of data on cognitive function in RA populations. Appenzeller, et al. observed cognitive impairment in 30.0% of RA patients and 7.5% of healthy controls
[11]. Patients with RA had worse outcomes in verbal fluency, logical memory and short-term
memory, while those with active disease had worse cognition scores. A psychometric
assessment of 30 patients with RA, which related performance to neuroimaging, found
an abnormal prevalence of impaired cognitive performance, particularly in attention
tasks, planning abilities and cognitive flexibility, and identified deficits related
to cortical function; visual memory was impaired in 50% and verbal memory in 35% [12]. Abnormalities on MRI were found with white matter hyperintensity in 35% of patients,
all of whom had low scores in attention, executive and visuospatial tests.

Fatigue is virtually ubiquitous in RA, part of which is a cognitive fatigue with lack
of clarity of thought and an inability to concentrate [2]. It often improves with biologic therapies, suggesting that aspects of fatigue are
centrally driven and mediated by TNF or interleukin-6 [3,13]. While pain and depression may underpin some of this relationship, fatigue is present
in as many as one third of RA patients with low levels of disease activity and lack
of clinical depression [14]. Our work reaffirms that the relationship between fatigue, cognition and disease
activity is a complex one, and that some aspects are responsive to therapy. The improvement
in performance IQ suggests that cognitive function alone needs to be carefully considered;
it may be independent of fatigue or it may be a subset of the symptom complex of fatigue,
with the exciting prospect that aspects of it are modifiable by treatment.

MRI did not reveal a physiological correlate of changes in cognitive function, although
fatigue at 3 months correlated with CBF in white and grey matter. We applied a pulsed
ASL sequence technique (FAIR), which allowed a noninvasive measurement of perfusion.
This is the first use of ASL in an RA cohort. Bartolini, et al. assessed perfusion with single-photon emission computed tomography and found 85% of
patients had hypoperfusion of the frontal lobes, with parietal lobe hypoperfusion
in 40%. Our study was designed specifically to detect longitudinal changes in CBF
as a function of treatment, and so does not allow cross-sectional quantitative assessment
of baseline regional perfusion differences. However, visual inspection of the CBF
data did not reveal any obvious frontal hypoperfusion in our group. Interestingly,
lower CBF correlated with lower levels of fatigue at 3 months, alongside a weak trend
for a reduction in CBF after 3 months of treatment with adalimumab. These data are
counterintuitive; our hypothesis was that TNF blockade would enhance CBF and this
enhancement would correlate with improvement in fatigue. However, we may have missed
any acute effects of treatment on CBF and would recommend imaging soon after treatment
initiation in future studies. Nonetheless, the inverse correlation between fatigue
and CBF at 3 months remains intriguing.

Conclusions

Our small pilot study has demonstrated an apparent improvement in cognitive function
with effective treatment of RA. We could not link changes in CBF with improved cognitive
function despite a possible influence on fatigue. Future studies need to address and
confirm the specificity of this treatment effect, as well as seeking earlier treatment-related
changes in CBF. The major challenge is to build a template for cognition and fatigue
in RA, with a view to establishing a more complete understanding of pathophysiological
influences, with the ultimate aim of identifying and directing effective treatment.

Competing interests

JDI received a speaker fee from Abbott in 2010. Other authors have no financial competing
interests.

Authors' contributions

GR, AMB, JLN and JDI were involved in study design. GR, JH, RP, JLN, AMB and JDI collected
and analysed data. GR, AMB, JLN and JDI wrote and edited the manuscript. DB reviewed
MRI scans. All authors have read and approved the manuscript for publication.

Acknowledgements

This work was supported in part by NIHR Newcastle Biomedical Research Centre. Funding
for this study was provided by Abbott Laboratories. Abbott Laboratories were not involved
in study design; in the collection, analysis and interpretation of data; or in the
writing of the report.